[1]马德仲,任锁,刘凯辛,等. 贝叶斯网络和模糊评判结合的滚动轴承故障诊断[J].哈尔滨理工大学学报,2018,(05):113-118.[doi:10.15938/j.jhust.2018.05.019]
 MA De zhong,REN Suo,LIU Kai xin,et al. Fault Diagnosis of Rolling Bearing Based on Bayesian Network and Fuzzy Evaluation[J].哈尔滨理工大学学报,2018,(05):113-118.[doi:10.15938/j.jhust.2018.05.019]
点击复制

 贝叶斯网络和模糊评判结合的滚动轴承故障诊断()
分享到:

《哈尔滨理工大学学报》[ISSN:1007-2683/CN:23-1404/N]

卷:
期数:
2018年05期
页码:
113-118
栏目:
测控技术与通信工程
出版日期:
2018-10-25

文章信息/Info

Title:
 Fault Diagnosis of Rolling Bearing Based on Bayesian Network and Fuzzy Evaluation
作者:
 马德仲任锁刘凯辛李明周真
 (哈尔滨理工大学 测控技术与通信工程学院,
测控技术与仪器黑龙江省高校重点实验室,黑龙江 哈尔滨 150080)
Author(s):
 MA DezhongREN SuoLIU KaixinLI MingZHOU Zhen
 (School of Measurementcontrol Technology and Communications Engineering, Harbin University of Science and Technology, 
The Higher Educational Key Laboratory for Measuring and Control Technology and Instrumentations of Heilongjiang Province, Harbin 150080, China)
关键词:
关键词:贝叶斯网络模糊综合评判诊断优化
Keywords:
 Keywords:bayesian network fuzzy comprehensive evaluation diagnostic optimization
分类号:
X9287
DOI:
10.15938/j.jhust.2018.05.019
文献标志码:
A
摘要:
摘要:针对大型复杂系统在诊断的过程中,由于现有方法主要通过一系列方法来提高诊断的效果,而缺乏考虑诊断过程中的检测难度、检测速度和检测经济性等因素。提出了贝叶斯网络诊断与多因素模糊综合评判相结合进行故障诊断的方法,在诊断的过程中不仅考虑故障概率,而且结合检测方法难易程度、检测速度、检测的准确性和经济性等方面,得到诊断的优化方法。通过对齿轮箱滚动轴承故障进行诊断的实例,可以明显看出该方法在综合诊断过程中的优势。研究成果可以作为对大型复杂系统进行故障诊断的优化方法,从而科学指导维修方案。
Abstract:
 Abstract:In the process of diagnosing large and complex system, the existing methods mainly improve the diagnosis effect by a series of methods, but lack the consideration of the difficulty of detection, the detection speed and the detection economyIn this paper, Bayesian network diagnosis and multifactor fuzzy comprehensive evaluation are combined to diagnose the fault In the process of diagnosis, not only the probability of failure is considered, but also the difficulty of detection, the speed of detection, the accuracy and economy of detection, and the optimization method is obtainedThe advantages of this method in the comprehensive diagnosis process can be clearly seen by the example of diagnosing the fault of gearbox bearingThe research results can be used as an optimization method for fault diagnosis of large and complex systems, so as to guide the maintenance plan scientifically

参考文献/References:

 [1]LIU Y J, MENG Q H, ZENG M, et al Fault Diagnosis Method Based on Probability Extended SDG and Fault Index[C]// World Congress on Intelligent Control and Automation 2016:2868-2873
[2]GHOSHAL S K, SAMANTARAY A K Bond Graph Modelbased Fault Diagnosis[J]. Bond Graph Modelling of Engineering Systems, 2011:227-265
[3]HE W, WANG Y, XING K, et al ErrorRate Estimation Based on MultiSignal Flow Graph Model and Accelerated Radiation Tests[J]. Plos One, 2016, 11(9):e0161378
[4]BALAKRISHNAN N Fault Tree Analysis for Medical Applications[J]. Dependability in Medicine & Neurology, 2015:83-112 
[5]MOUSAZADEH S, COHEN I Embedding and Function Extension on Directed Graph[J]. Signal Processing, 2015, 111(C):137-149 
[6]LIU Z, LIU Y, SHAN H, et al A Fault Diagnosis Methodology for Gear Pump Based on EEMD and Bayesian Network[J]. Plos One, 2015, 10(5):e0125703
[7]韩璞, 张德利, 韩晓娟,等 基于主成分分析法与贝叶斯网络的汽轮机故障诊断方法[J]. 热能动力工程, 2008, 23(3):244-247
[8]仝兆景, 石秀华, 王文斌,等 基于优化分簇贝叶斯网的转子振动故障诊断[J]. 振动、测试与诊断, 2014, 34(2):237-241
[9]张歆炀, 帕孜来·马合木提,等 基于故障树与键合图的贝叶斯网络故障诊断[J]. 电测与仪表, 2016, 53(2):21-26
[10]杨承刚, 朝格图胡日都, 李茂林,等 汽轮机故障树诊断方法研究及应用[J]. 装备制造技术, 2014(11):50-54
[11]卿黎, 张胜跃, 张宇栋,等 电站锅炉承压部件失效模式分析[J]. 安全与环境学报, 2016(4):17-22
[12]沈琳, 于劲松, 唐荻音,等 图模型与学习算法结合的贝叶斯网络自动建模[J]. 北京航空航天大学学报, 2016, 42(7):1486-1493
[13]邱小平, 刘亚龙, 马丽娜,等 基于贝叶斯网络的车辆换道模型[J]. 交通运输系统工程与信息, 2015, 15(5):67-73
[14]蔡朝晖, 张健沛, 杨静 基于贝叶斯网络的路网位置匿名区域估计[J]. 吉林大学学报(工), 2014, 44(2):454-458
[15]任岩, 毕亚雄, 王德宽,等 风电机组传动链的故障树智能诊断技术[J]. 排灌机械工程学报, 2016(4):328-331
[16]HU XX,WANG H,WANG S,etcUsing Expert’s Knowledge to Build Bayesian Networks[C]. Harbin 2007 International Conference on Computational Intelligence and Security Workshops,2007:220-223
[17]马德仲, 周真, 于晓洋,等 基于模糊概率的多状态贝叶斯网络可靠性分析[J]. 系统工程与电子技术, 2012, 34(12):2607-2611
[18]张华杰 三角形隶属度函数模糊神经在肺癌诊断中的应用(英文)[J]. 生物技术世界, 2013(4):69-70
[19]张金彪 基于贝叶斯网络的风力发电机齿轮箱故障分析[D]. 哈尔滨:哈尔滨理工大学, 2012
[20]孙凯帆, 阚树林, 曹召锋,等 基于模糊FMECA的液压系统可靠性分析[J]. 液压气动与密封, 2014, 34(5):26-29

相似文献/References:

[1]赵辉,赵璐.多级模糊综合评判在招聘幼儿教师中的应用[J].哈尔滨理工大学学报,2017,(02):90.[doi:10.15938/j.jhust.2017.02.017]
 ZHAOuiZHAO Lu.The Application of Fuzzy Comprehensive Evaluationin the Recruitment of Kindergarten Teachers[J].哈尔滨理工大学学报,2017,(05):90.[doi:10.15938/j.jhust.2017.02.017]

备注/Memo

备注/Memo:
 基金项目:黑龙江省自然科学基金面上项目(F201305)
更新日期/Last Update: 2018-11-14